Statistical Analysis of High-Level Features from State of the Union Addresses

Trevor J. Bihl and Kenneth W. Bauer
Additional contact information
Trevor J. Bihl: Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, OH, USA
Kenneth W. Bauer: Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, OH, USA

International Journal of Information Systems and Social Change (IJISSC), 2017, vol. 8, issue 2, 50-73

Abstract: A computational political science approach is taken to analyze the State of the Union Addresses (SUA) from 1790 to 2015. While low-level features, e.g. linguistic characteristics, are commonly used for lexical analysis, the authors herein illustrate the utility of high-level features, e.g. Flesch-Kincaid readability, for knowledge discovery and discrimination between types of speeches. A process is developed and employed to exploit high-level features which employs 1) statistical clustering (k-means) and a literature review to define types of speeches (e.g. written or oral), 2) classification methods via logistic regression to examine the validity of the defined classes, and 3) classifier-based feature selection to determine salient features. Recent interest in the SUA has posited that changes in readability in the SUA are due to declining audience capabilities; however, the authors' results show that changes in readability are a reflection of changes in the SUA delivery medium.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJISSC.2017040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jissc0:v:8:y:2017:i:2:p:50-73

Access Statistics for this article

International Journal of Information Systems and Social Change (IJISSC) is currently edited by John Wang

More articles in International Journal of Information Systems and Social Change (IJISSC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().